A Comparative Study of Scheduling Techniques for Multimedia Applications on SIMD Pipelines

Parallel architectures are essential in order to take advantage of the parallelism inherent in streaming applications. One particular branch of these employ hardware SIMD pipelines. In this paper, we analyse several scheduling techniques, namely ad hoc overlapped execution, modulo scheduling and modulo scheduling with unrolling, all of which aim to efficiently utilize the special architecture design. Our investigation focuses on improving throughput while analysing other metrics that are important for streaming applications, such as register pressure, buffer sizes and code size. Through experiments conducted on several media benchmarks, we present and discuss trade-offs involved when selecting any one of these scheduling techniques.Comment: Presented at DATE Friday Workshop on Heterogeneous Architectures and Design Methods for Embedded Image Systems (HIS 2015) (arXiv:1502.07241

Modulo scheduling for a fully-distributed clustered VLIW architecture

Clustering is an approach that many microprocessors are adopting in recent times in order to mitigate the increasing penalties of wire delays. We propose a novel clustered VLIW architecture which has all its resources partitioned among clusters, including the cache memory. A modulo scheduling scheme for this architecture is also proposed. This algorithm takes into account both register and memory inter-cluster communications so that the final schedule results in a cluster assignment that favors cluster locality in cache references and register accesses. It has been evaluated for both 2- and 4-cluster configurations and for differing numbers and latencies of inter-cluster buses. The proposed algorithm produces schedules with very low communication requirements and outperforms previous cluster-oriented schedulers.Peer ReviewedPostprint (published version

Widening resources: a cost-effective technique for aggressive ILP architectures

The inherent instruction-level parallelism (ILP) of current applications (specially those based on floating point computations) has driven hardware designers and compilers writers to investigate aggressive techniques for exploiting program parallelism at the lowest level. To execute more operations per cycle, many processors are designed with growing degrees of resource replication (buses and functional units). However the high cost in terms of area and cycle time of this technique precludes the use of high degrees of replication. An alternative to resource replication is resource widening, that has also been used in some recent designs, in which the width of the resources is increased. In this paper we evaluate a broad set of design alternatives that combine both replication and widening. For each alternative we perform an estimation of the ILP limits (including the impact of spill code for several register file configurations) and the cost in terms of area and access time of the register file. We also perform a technological projection for the next 10 years in order to foresee the possible implementable alternatives. From this study we conclude that if the cost is taken into account, the best performance is obtained when combining certain degrees of replication and widening in the hardware resources. The results have been obtained from a large number of inner loops from numerical programs scheduled for VLIW architecturesPeer ReviewedPostprint (published version

Recursos anchos: una técnica de bajo coste para explotar paralelismo agresivo en códigos numéricos

Els bucles son la part que més temps consumeix en les aplicacions numèriques. El rendiment dels bucles està limitat tant pels recursos oferts per l'arquitectura com per les recurrències del bucle en la computació. Per executar més operacions per cicle, els processadors actuals es dissenyen amb graus creixents de replicació de recursos (tècnica de replicació) para ports de memòria i unitats funcionals. En canvi, el gran cost en termes d'àrea i temps de cicle d'aquesta tècnica limita tenir alts graus de replicació: alts valors en temps de cicle contraresten els guanys deguts al decrement en el nombre de cicles, mentre que alts valors en l'àrea requerida poden portar a configuracions impossibles d'implementar. Una alternativa a la replicació de recursos, és fer los més amples (tècnica que anomenem "widening"), i que ha estat usada en alguns dissenys recents. Amb aquesta tècnica, l'amplitud dels recursos s'amplia, fent una mateixa operació sobre múltiples dades. Per altra banda, alguns microprocessadors escalars de propòsit general han estat implementats amb unitats de coma flotants que implementen la instrucció sumar i multiplicar unificada (tècnica de fusió), el que redueix la latència de la operació combinada, tanmateix com el nombre de recursos utilitzats. A aquest treball s'avaluen un ampli conjunt d'alternatives de disseny de processadors VLIW que combinen les tres tècniques. S'efectua una projecció tecnològica de les noves generacions de processadors per predir les possibles alternatives implementables. Com a conclusió, demostrem que tenint en compte el cost, combinar certs graus de replicació i "widening" als recursos hardware és més efectiu que aplicar únicament replicació. Així mateix, confirmem que fer servir unitats que fusionen multiplicació i suma pot tenir un impacte molt significatiu en l'increment de rendiment en futures arquitectures de processadors a un cost molt raonable.Loops are the main time-consuming part of numerical applications. The performance of the loops is limited either by the resources offered by the architecture or by recurrences in the computation. To execute more operations per cycle, current processors are designed with growing degrees of resource replication (replication technique) for memory ports and functional units. However, the high cost in terms of area and cycle time of this technique precludes the use of high degrees of replication. High values for the cycle time may clearly offset any gain in terms of number of execution cycles. High values for the area may lead to an unimplementable configuration. An alternative to resource replication is resource widening (widening technique), which has also been used in some recent designs in which the width of the resources is increased (i.e., a single operation is performed over multiple data). Moreover, several general-purpose superscalar microprocessors have been implemented with multiply-add fused floating point units (fusion technique), which reduces the latency of the combined operation and the number of resources used. On this thesis, we evaluate a broad set of VLIW processor design alternatives that combine the three techniques. We perform a technological projection for the next processor generations in order to foresee the possible implementable alternatives. From this study, we conclude that if the cost is taken into account, combining certain degrees of replication and widening in the hardware resources is more effective than applying only replication. Also, we confirm that multiply-add fused units will have a significant impact in raising the performance of future processor architectures with a reasonable increase in cost

Accelerating SPICE Model-Evaluation using FPGAs

Single-FPGA spatial implementations can provide an order of magnitude speedup over sequential microprocessor implementations for data-parallel, floating-point computation in SPICE model-evaluation. Model-evaluation is a key component of the SPICE circuit simulator and it is characterized by large irregular floating-point compute graphs. We show how to exploit the parallelism available in these graphs on single-FPGA designs with a low-overhead VLIW-scheduled architecture. Our architecture uses spatial floating-point operators coupled to local high-bandwidth memories and interconnected by a time-shared network. We retime operation inputs in the model-evaluation to allow independent scheduling of computation and communication. With this approach, we demonstrate speedups of 2–18× over a dual-core 3GHz Intel Xeon 5160 when using a Xilinx Virtex 5 LX330T for a variety of SPICE device models

Instruction scheduling for clustered vliw architectures

Abstrac

Packet Transactions: High-level Programming for Line-Rate Switches

Many algorithms for congestion control, scheduling, network measurement, active queue management, security, and load balancing require custom processing of packets as they traverse the data plane of a network switch. To run at line rate, these data-plane algorithms must be in hardware. With today's switch hardware, algorithms cannot be changed, nor new algorithms installed, after a switch has been built. This paper shows how to program data-plane algorithms in a high-level language and compile those programs into low-level microcode that can run on emerging programmable line-rate switching chipsets. The key challenge is that these algorithms create and modify algorithmic state. The key idea to achieve line-rate programmability for stateful algorithms is the notion of a packet transaction : a sequential code block that is atomic and isolated from other such code blocks. We have developed this idea in Domino, a C-like imperative language to express data-plane algorithms. We show with many examples that Domino provides a convenient and natural way to express sophisticated data-plane algorithms, and show that these algorithms can be run at line rate with modest estimated die-area overhead.Comment: 16 page

MERCURY: Accelerating DNN Training By Exploiting Input Similarity

Deep Neural Networks (DNN) are computationally intensive to train. It consists of a large number of multidimensional dot products between many weights and input vectors. However, there can be significant similarity among input vectors. If one input vector is similar to another, its computations with the weights are similar to those of the other and, therefore, can be skipped by reusing the already-computed results. We propose a novel scheme, called MERCURY, to exploit input similarity during DNN training in a hardware accelerator. MERCURY uses Random Projection with Quantization (RPQ) to convert an input vector to a bit sequence, called Signature. A cache (MCACHE) stores signatures of recent input vectors along with the computed results. If the Signature of a new input vector matches that of an already existing vector in the MCACHE, the two vectors are found to have similarities. Therefore, the already-computed result is reused for the new vector. To the best of our knowledge, MERCURY is the first work that exploits input similarity using RPQ for accelerating DNN training in hardware. The paper presents a detailed design, workflow, and implementation of the MERCURY. Our experimental evaluation with twelve different deep learning models shows that MERCURY saves a significant number of computations and speeds up the model training by an average of 1.97X with an accuracy similar to the baseline system.Comment: 13 pages, 18 figures, 4 table

Heuristics for register-constrained software pipelining

Software Pipelining is a loop scheduling technique that extracts parallelism from loops by overlapping the execution of several consecutive iterations. There has been a significant effort to produce throughput-optimal schedules under resource constraints, and more recently to produce throughput-optimal schedules with minimum register requirements. Unfortunately even a throughput-optimal schedule with minimum register requirements is useless if it requires more registers than those available in the target machine. This paper evaluates several techniques for producing register-constrained modulo schedules: increasing the initiation interval (II) and adding spill code. We show that, in general, increasing the II performs poorly and might not converge for some loops. The paper also presents an iterative spilling mechanism that can be applied to any software pipelining technique and proposes several heuristics in order to speed-up the scheduling processPeer ReviewedPostprint (published version